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Active learning methods for biophysical parameter estimation / Edoardo Pasolli in IEEE Transactions on geoscience and remote sensing, vol 50 n° 10 Tome 2 (October 2012)
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Titre : Active learning methods for biophysical parameter estimation Type de document : Article/Communication Auteurs : Edoardo Pasolli, Auteur ; F. Melgani, Auteur ; N. Alajlan, Auteur ; B. Yakoub, Auteur Année de publication : 2012 Article en page(s) : pp 4071 - 4084 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] algorithme de Gauss
[Termes IGN] apprentissage automatique
[Termes IGN] chlorophylle
[Termes IGN] régression
[Termes IGN] séparateur à vaste marge
[Termes IGN] variable biophysique (végétation)Résumé : (Auteur) In this paper, we face the problem of collecting training samples for regression problems under an active learning perspective. In particular, we propose various active learning strategies specifically developed for regression approaches based on Gaussian processes (GPs) and support vector machines (SVMs). For GP regression, the first two strategies are based on the idea of adding samples that are dissimilar from the current training samples in terms of covariance measure, while the third one uses a pool of regressors in order to select the samples with the greater disagreements between the different regressors. Finally, the last strategy exploits an intrinsic GP regression outcome to pick up the most difficult and hence interesting samples to label. For SVM regression, the method based on the pool of regressors and two additional strategies based on the selection of the samples distant from the current support vectors in the kernel-induced feature space are proposed. The experimental results obtained on simulated and real data sets show that the proposed strategies exhibit a good capability to select samples that are significant for the regression process, thus opening the way to the active learning approach for remote-sensing regression problems. Numéro de notice : A2012-528 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2187906 Date de publication en ligne : 17/04/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2187906 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31974
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 10 Tome 2 (October 2012) . - pp 4071 - 4084[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012101B MANQUANT Revue Centre de documentation Indéterminé Disponible A complete processing chain for shadow detection and reconstruction in VHR images / L. Lorenzi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 9 (October 2012)
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Titre : A complete processing chain for shadow detection and reconstruction in VHR images Type de document : Article/Communication Auteurs : L. Lorenzi, Auteur ; F. Melgani, Auteur ; Grégoire Mercier, Auteur Année de publication : 2012 Article en page(s) : pp 3440 - 3452 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection d'ombre
[Termes IGN] image à très haute résolution
[Termes IGN] interpolation linéaire
[Termes IGN] reconstruction d'image
[Termes IGN] régression linéaireRésumé : (Auteur) The presence of shadows in very high resolution (VHR) images can represent a serious obstacle for their full exploitation. This paper proposes to face this problem as a whole through the proposal of a complete processing chain, which relies on various advanced image processing and pattern recognition tools. The first key point of the chain is that shadow areas are not only detected but also classified to allow their customized compensation. The detection and classification tasks are implemented by means of the state-of-the-art support vector machine approach. A quality check mechanism is integrated in order to reduce subsequent misreconstruction problems. The reconstruction is based on a linear regression method to compensate shadow regions by adjusting the intensities of the shaded pixels according to the statistical characteristics of the corresponding nonshadow regions. Moreover, borders are explicitly handled by making use of adaptive morphological filters and linear interpolation for the prevention of possible border artifacts in the reconstructed image. Experimental results obtained on three VHR images representing different shadow conditions are reported, discussed, and compared with two other reconstruction techniques. Numéro de notice : A2012-450 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2183876 Date de publication en ligne : 05/03/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2183876 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31896
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 9 (October 2012) . - pp 3440 - 3452[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2012091 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Integration of remote sensing and GIS for evaluating soil erosion risk in northwestern Zhejiang, China / Jianqin Huang in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 9 (September 2012)
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Titre : Integration of remote sensing and GIS for evaluating soil erosion risk in northwestern Zhejiang, China Type de document : Article/Communication Auteurs : Jianqin Huang, Auteur ; Dong Lu, Auteur ; Jin Li, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 935 - 946 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte pédologique
[Termes IGN] Chine
[Termes IGN] écosystème forestier
[Termes IGN] érosion
[Termes IGN] estimation statistique
[Termes IGN] forêt tropicale
[Termes IGN] gradient de pente
[Termes IGN] image Landsat-TM
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle RUSLE
[Termes IGN] régression multiple
[Termes IGN] risque naturel
[Termes IGN] système d'information géographiqueRésumé : (Auteur) Estimation of soil loss using the Revised Universal Soil Loss Equation (rusle) has long been an active research topic, but its application in a large area is a challenge due to data availability and quality. In this study, the RUSLE model was used to evaluate soil erosion risk based on soil samples, a soil type map, digital elevation model (dem) data, and Landsat Thematic Mapper (tm) images. Multiple regression analysis was used to identify major factors influencing soil erosion risks. A regression model based on DEM-derived slope gradient and TM-derived fractional soil and vegetation images was developed to map soil erosion risk distribution in a forest ecosystem in Zhejiang, China. The developed method has the potential to quickly examine spatial distri-bution of soil erosion risks. This study provides a new insight for evaluating soil erosion risks in forest ecosystems with the integration of remote sensing and GIS. Numéro de notice : A2012-441 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.14358/PERS.78.9.935 En ligne : https://doi.org/10.14358/PERS.78.9.935 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31887
in Photogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 9 (September 2012) . - pp 935 - 946[article]The affine constrained GNSS attitude model and its multivariate integer least-squares solution / Peter J.G. Teunissen in Journal of geodesy, vol 86 n° 7 (July 2012)
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Titre : The affine constrained GNSS attitude model and its multivariate integer least-squares solution Type de document : Article/Communication Auteurs : Peter J.G. Teunissen, Auteur Année de publication : 2012 Article en page(s) : pp 547 - 563 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] affaiblissement de la précision
[Termes IGN] antenne GNSS
[Termes IGN] méthode des moindres carrés
[Termes IGN] phase GNSS
[Termes IGN] précision du positionnement
[Termes IGN] résolution d'ambiguïtéRésumé : (Auteur) A new global navigation satellite system (GNSS) carrier-phase attitude model and its solution are introduced in this contribution. This affine-constrained GNSS attitude model has the advantage that it avoids the computational complexity of the orthonormality-constrained GNSS attitude model, while it still has a significantly improved ambiguity resolution performance over its unconstrained counterpart. The functional and stochastic model is formulated in multivariate form, for one-, two- and three-dimensional antenna arrays, tracking GNSS signals on an arbitrary number of frequencies with two or more antennas. The stochastic model includes the capability to capture variations in the antenna-quality within the array. The multivariate integer least-squares solution of the model parameters is given and the model’s ambiguity success-rate is analysed by means of the ambiguity dilution of precision (ADOP). A general closed-form expression for the affine-constrained ADOP is derived, thus providing an easy-to-use and insightful rule-of-thumb for the ambiguity resolution capabilities of the affine constrained GNSS attitude model. Numéro de notice : A2012-357 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-011-0538-z Date de publication en ligne : 28/12/2011 En ligne : https://doi.org/10.1007/s00190-011-0538-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31803
in Journal of geodesy > vol 86 n° 7 (July 2012) . - pp 547 - 563[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 266-2012071 RAB Revue Centre de documentation En réserve L003 Disponible The potential of spectral mixture analysis to improve the estimation accuracy of tropical forest biomass / T.M. Basuki in Geocarto international, vol 27 n° 4 (July 2012)
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Titre : The potential of spectral mixture analysis to improve the estimation accuracy of tropical forest biomass Type de document : Article/Communication Auteurs : T.M. Basuki, Auteur ; Andrew K. Skidmore, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 329 - 345 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] biomasse
[Termes IGN] estimation statistique
[Termes IGN] forêt tropicale
[Termes IGN] image Landsat-ETM+
[Termes IGN] Indonésie
[Termes IGN] régressionRésumé : (Auteur) A main limitation of pixel-based vegetation indices or reflectance values for estimating above-ground biomass is that they do not consider the mixed spectral components on the earth's surface covered by a pixel. In this research, we decomposed mixed reflectance in each pixel before developing models to achieve higher accuracy in above-ground biomass estimation. Spectral mixture analysis was applied to decompose the mixed spectral components of Landsat-7 ETM+ imagery into fractional images. Afterwards, regression models were developed by integrating training data and fraction images. The results showed that the spectral mixture analysis improved the accuracy of biomass estimation of Dipterocarp forests. When applied to the independent validation data set, the model based on the vegetation fraction reduced 5–16% the root mean square error compared to the models using a single band 4 or 5, multiple bands 4, 5, 7 and all non-thermal bands of Landsat ETM+. Numéro de notice : A2012-334 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2011.634928 Date de publication en ligne : 05/12/2011 En ligne : https://doi.org/10.1080/10106049.2011.634928 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31780
in Geocarto international > vol 27 n° 4 (July 2012) . - pp 329 - 345[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2012041 RAB Revue Centre de documentation En réserve L003 Disponible 3-D mapping of a multi-layered Mediterranean forest using ALS data / António Ferraz in Remote sensing of environment, vol 121 (June 2012)
PermalinkVisibility monitoring using conventional roadside cameras : Emerging applications / Raouf Babari in Transportation Research - Part C: Emerging Technologies, vol 22 (June 2012)
PermalinkTracking human impact on current tree species distribution using plant communities / Daniel E. Silva in Journal of vegetation science, vol 23 n° 2 (April 2012)
PermalinkDoes natural regeneration determine the limit of European beech distribution under climatic stress? / Daniel E. Silva in Forest ecology and management, vol 266 (15 February 2012)
PermalinkCarbon Stock of European Beech Forest : A Case at M. Pizzalto, Italy / Aida Taghavi Bayat in APCBEE Procedia, vol 1 (2-20)
PermalinkFast integer least-squares estimation for GNSS high-dimensional ambiguity resolution using lattice theory / S. Jazaeri in Journal of geodesy, vol 86 n° 2 (February 2012)
PermalinkCartographie du déboisement à partir de données à haute résolution spatiale / Yannick Philippets (2012)
PermalinkComparing small-footprint lidar and forest inventory data for single strata biomass estimation : A case study over a multi-layered mediterranean forest / António Ferraz (2012)
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PermalinkPermalinkPhotogrammetric techniques for voxel-based flow velocity field measurement / Patrick Westfeld in Photogrammetric record, vol 26 n° 136 (December 2011 - February 2012)
PermalinkRelevance assessment of full-waveform lidar data for urban area classification / Clément Mallet in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 6 supplement (December 2011)
PermalinkA volumetric approach to population estimation using lidar remote sensing / Zhong Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 11 (November 2011)
PermalinkEstimation of forest stand volume, tree density and biodiversity using Landsat ETM + Data, comparison of linear and regression tree analyses / Jahangir Mohammadi in Procedia Environmental Sciences, vol 7 (2011)
PermalinkPrediction of the error induced by topography in satellite microwave radiometric observations / Luca Pulvirenti in IEEE Transactions on geoscience and remote sensing, vol 49 n° 9 (September 2011)
PermalinkMining boundary effects in areally referenced spatial data using the Bayesian information criterion / Sudipto Banerjee in Geoinformatica, vol 15 n° 3 (July 2011)
PermalinkEstimation de la pesanteur terrestre par gravimétrie mobile / B. Li in Bulletin d'information scientifique et technique de l'IGN, n° 77 (avril 2011)
PermalinkPermalinkPermalinkEpipolar arrangement of satellite imagery by projection trajectory simplification / M. Wang in Photogrammetric record, vol 25 n° 132 (December 2010 - February 2011)
PermalinkComparison of matching algorithms for DSM generation in urban areas from ikonos imagery / A. Alobeid in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 9 (September 2010)
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